SlideShare a Scribd company logo

week14_segmentation.pdf

•
•
Y
YuChianWu

1

Engineering
1 of 37
Download to read offline
Segmentation Vladislav Goncharenko Spring 2019 MIPT, Moscow
Outline ● Segmentation task ● Simple solutions ● Upsampling methods ○ Unpooling ○ Transposed convolution ● FCN ● DeconvNet ● SegNet ● U-Net ● Mask R-CNN
Semantic Segmentation Input image (C x H x W) Output mask of classes (1 x H x W) Assumption just class label for each pixel
Instance Segmentation Input image (C x H x W) Output mask of class instances (detection + 1 x H x W) Assumption separated masks for each distinct object
Naive solution Problem: Very inefficient! Not reusing shared features between overlapping patches (same as R-CNN)
Fully Convolutional Problem: convolutions at original image resolution will be very expensive (remember VGG architecture)
Downsampling and Upsampling
Simple unpooling
Max Unpooling
Regular convolution Images credentials
Regular convolution: matrix form
Regular convolution: matrix form
Transposed convolution matrix
Convolution as Matrix Multiplication (1D)
Terms Some researchers denote Transposed convolution with term “Deconvolution”. However: deconvolution is an algorithm-based process used to reverse the effects of convolution on recorded data [Wikipedia] What we do is not a deconvolution. Please be precise in terms Right terms: ● Transposed convolution ● Upconvolution
FCN - Fully Convolutional Network
Regular CNN to FCN
Regular CNN to FCN
Regular CNN to FCN Problem: we lose resolution
FCN: Introduce skip connections
FCN: Results
DeconvNet: use Max Unpooling
DeconvNet: use Max Unpooling
DeconvNet: use Max Unpooling
SegNet: Further development
SegNet: Further development
U-Net
U-Net
U-Net
Mask R-CNN: Instance segmentation
Mask R-CNN
Mask R-CNN: RoI Align
Mask R-CNN: Results
Bonus: Pose estimation
Bonus: Pose estimation
Revise ● Segmentation task ● Simple solutions ● Upsampling methods ○ Unpooling ○ Transposed convolution ● FCN ● DeconvNet ● SegNet ● U-Net ● Mask R-CNN
Next time ● Variational AutoEncoders ● GANs Interactive playground for image generation

Recommended

Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)
Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)
Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)Universitat Politècnica de Catalunya
 
Alberto Massidda - Scenes from a memory - Codemotion Rome 2019
Alberto Massidda - Scenes from a memory - Codemotion Rome 2019Alberto Massidda - Scenes from a memory - Codemotion Rome 2019
Alberto Massidda - Scenes from a memory - Codemotion Rome 2019Codemotion
 
Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)
Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)
Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)Universitat Politècnica de Catalunya
 
PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018
PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018
PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018Universitat Politècnica de Catalunya
 
You only look once (YOLO) : unified real time object detection
You only look once (YOLO) : unified real time object detectionYou only look once (YOLO) : unified real time object detection
You only look once (YOLO) : unified real time object detectionEntrepreneur / Startup
 
物件偵測與辨識技術
物件偵測與辨識技術物件偵測與辨識技術
物件偵測與辨識技術CHENHuiMei
 
Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018
Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018
Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018Universitat Politècnica de Catalunya
 
Conditional Image Generation with PixelCNN Decoders
Conditional Image Generation with PixelCNN DecodersConditional Image Generation with PixelCNN Decoders
Conditional Image Generation with PixelCNN Decoderssuga93
 

Recommended

Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)
Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)
Image Segmentation (D3L1 2017 UPC Deep Learning for Computer Vision)Universitat Politècnica de Catalunya
 
Alberto Massidda - Scenes from a memory - Codemotion Rome 2019
Alberto Massidda - Scenes from a memory - Codemotion Rome 2019Alberto Massidda - Scenes from a memory - Codemotion Rome 2019
Alberto Massidda - Scenes from a memory - Codemotion Rome 2019Codemotion
 
Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)
Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)
Object Segmentation (D2L7 Insight@DCU Machine Learning Workshop 2017)Universitat Politècnica de Catalunya
 
PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018
PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018
PixelCNN, Wavenet, Normalizing Flows - Santiago Pascual - UPC Barcelona 2018Universitat Politècnica de Catalunya
 
You only look once (YOLO) : unified real time object detection
You only look once (YOLO) : unified real time object detectionYou only look once (YOLO) : unified real time object detection
You only look once (YOLO) : unified real time object detectionEntrepreneur / Startup
 
物件偵測與辨識技術
物件偵測與辨識技術物件偵測與辨識技術
物件偵測與辨識技術CHENHuiMei
 
Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018
Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018
Semantic Segmentation - Míriam Bellver - UPC Barcelona 2018Universitat Politècnica de Catalunya
 
Conditional Image Generation with PixelCNN Decoders
Conditional Image Generation with PixelCNN DecodersConditional Image Generation with PixelCNN Decoders
Conditional Image Generation with PixelCNN Decoderssuga93
 
Pixel RNN to Pixel CNN++
Pixel RNN to Pixel CNN++Pixel RNN to Pixel CNN++
Pixel RNN to Pixel CNN++Dongheon Lee
 
The reversible residual network
The reversible residual networkThe reversible residual network
The reversible residual networkThyrixYang1
 
Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)
Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)
Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)Universitat Politècnica de Catalunya
 
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...PyData
 
Dissecting the Rendering of The Surge
Dissecting the Rendering of The SurgeDissecting the Rendering of The Surge
Dissecting the Rendering of The SurgePhilip Hammer
 
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...Artem Lutov
 
PR-297: Training data-efficient image transformers & distillation through att...
PR-297: Training data-efficient image transformers & distillation through att...PR-297: Training data-efficient image transformers & distillation through att...
PR-297: Training data-efficient image transformers & distillation through att...Jinwon Lee
 
Recurrent Instance Segmentation (UPC Reading Group)
Recurrent Instance Segmentation (UPC Reading Group)Recurrent Instance Segmentation (UPC Reading Group)
Recurrent Instance Segmentation (UPC Reading Group)Universitat Politècnica de Catalunya
 
CyberSec_JPEGcompressionForensics.pdf
CyberSec_JPEGcompressionForensics.pdfCyberSec_JPEGcompressionForensics.pdf
CyberSec_JPEGcompressionForensics.pdfMohammadAzreeYahaya
 
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)Matthew O'Toole
 
Semantic Segmentation - Fully Convolutional Networks for Semantic Segmentation
Semantic Segmentation - Fully Convolutional Networks for Semantic SegmentationSemantic Segmentation - Fully Convolutional Networks for Semantic Segmentation
Semantic Segmentation - Fully Convolutional Networks for Semantic Segmentation岳華 杜
 
TAME: Trainable Attention Mechanism for Explanations
TAME: Trainable Attention Mechanism for ExplanationsTAME: Trainable Attention Mechanism for Explanations
TAME: Trainable Attention Mechanism for ExplanationsVasileiosMezaris
 
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)Universitat Politècnica de Catalunya
 
Overview of Convolutional Neural Networks
Overview of Convolutional Neural NetworksOverview of Convolutional Neural Networks
Overview of Convolutional Neural Networksananth
 
1-pytorch-CNN-RNN.pdf
1-pytorch-CNN-RNN.pdf1-pytorch-CNN-RNN.pdf
1-pytorch-CNN-RNN.pdfAndrey63387
 
Mask-RCNN for Instance Segmentation
Mask-RCNN for Instance SegmentationMask-RCNN for Instance Segmentation
Mask-RCNN for Instance SegmentationDat Nguyen
 
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...Universitat Politècnica de Catalunya
 
Spatial Filtering in intro image processingr
Spatial Filtering in intro image processingrSpatial Filtering in intro image processingr
Spatial Filtering in intro image processingrkumarankit06875
 
Deep learning for image video processing
Deep learning for image video processingDeep learning for image video processing
Deep learning for image video processingYu Huang
 
A brief introduction to recent segmentation methods
A brief introduction to recent segmentation methodsA brief introduction to recent segmentation methods
A brief introduction to recent segmentation methodsShunta Saito
 
lecture04_mle_svm_multiclass_pca.pdf
lecture04_mle_svm_multiclass_pca.pdflecture04_mle_svm_multiclass_pca.pdf
lecture04_mle_svm_multiclass_pca.pdfYuChianWu
 
lecture02_LinearRegression.pdf
lecture02_LinearRegression.pdflecture02_LinearRegression.pdf
lecture02_LinearRegression.pdfYuChianWu
 

More Related Content

Similar to week14_segmentation.pdf

Pixel RNN to Pixel CNN++
Pixel RNN to Pixel CNN++Pixel RNN to Pixel CNN++
Pixel RNN to Pixel CNN++Dongheon Lee
 
The reversible residual network
The reversible residual networkThe reversible residual network
The reversible residual networkThyrixYang1
 
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...PyData
 
Dissecting the Rendering of The Surge
Dissecting the Rendering of The SurgeDissecting the Rendering of The Surge
Dissecting the Rendering of The SurgePhilip Hammer
 
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...Artem Lutov
 
PR-297: Training data-efficient image transformers & distillation through att...
PR-297: Training data-efficient image transformers & distillation through att...PR-297: Training data-efficient image transformers & distillation through att...
PR-297: Training data-efficient image transformers & distillation through att...Jinwon Lee
 
CyberSec_JPEGcompressionForensics.pdf
CyberSec_JPEGcompressionForensics.pdfCyberSec_JPEGcompressionForensics.pdf
CyberSec_JPEGcompressionForensics.pdfMohammadAzreeYahaya
 
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)Matthew O'Toole
 
Semantic Segmentation - Fully Convolutional Networks for Semantic Segmentation
Semantic Segmentation - Fully Convolutional Networks for Semantic SegmentationSemantic Segmentation - Fully Convolutional Networks for Semantic Segmentation
Semantic Segmentation - Fully Convolutional Networks for Semantic Segmentation岳華 杜
 
TAME: Trainable Attention Mechanism for Explanations
TAME: Trainable Attention Mechanism for ExplanationsTAME: Trainable Attention Mechanism for Explanations
TAME: Trainable Attention Mechanism for ExplanationsVasileiosMezaris
 
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)Universitat Politècnica de Catalunya
 
Overview of Convolutional Neural Networks
Overview of Convolutional Neural NetworksOverview of Convolutional Neural Networks
Overview of Convolutional Neural Networksananth
 
1-pytorch-CNN-RNN.pdf
1-pytorch-CNN-RNN.pdf1-pytorch-CNN-RNN.pdf
1-pytorch-CNN-RNN.pdfAndrey63387
 
Mask-RCNN for Instance Segmentation
Mask-RCNN for Instance SegmentationMask-RCNN for Instance Segmentation
Mask-RCNN for Instance SegmentationDat Nguyen
 
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...Universitat Politècnica de Catalunya
 
Spatial Filtering in intro image processingr
Spatial Filtering in intro image processingrSpatial Filtering in intro image processingr
Spatial Filtering in intro image processingrkumarankit06875
 
Deep learning for image video processing
Deep learning for image video processingDeep learning for image video processing
Deep learning for image video processingYu Huang
 
A brief introduction to recent segmentation methods
A brief introduction to recent segmentation methodsA brief introduction to recent segmentation methods
A brief introduction to recent segmentation methodsShunta Saito
 

Similar to week14_segmentation.pdf (20)

Pixel RNN to Pixel CNN++
Pixel RNN to Pixel CNN++Pixel RNN to Pixel CNN++
Pixel RNN to Pixel CNN++
 
The reversible residual network
The reversible residual networkThe reversible residual network
The reversible residual network
 
Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)
Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)
Deep Learning for Computer Vision: Unsupervised Learning (UPC 2016)
 
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...
The Face of Nanomaterials: Insightful Classification Using Deep Learning - An...
 
Dissecting the Rendering of The Surge
Dissecting the Rendering of The SurgeDissecting the Rendering of The Surge
Dissecting the Rendering of The Surge
 
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...
DAOR - Bridging the Gap between Community and Node Representations: Graph Emb...
 
PR-297: Training data-efficient image transformers & distillation through att...
PR-297: Training data-efficient image transformers & distillation through att...PR-297: Training data-efficient image transformers & distillation through att...
PR-297: Training data-efficient image transformers & distillation through att...
 
Recurrent Instance Segmentation (UPC Reading Group)
Recurrent Instance Segmentation (UPC Reading Group)Recurrent Instance Segmentation (UPC Reading Group)
Recurrent Instance Segmentation (UPC Reading Group)
 
CyberSec_JPEGcompressionForensics.pdf
CyberSec_JPEGcompressionForensics.pdfCyberSec_JPEGcompressionForensics.pdf
CyberSec_JPEGcompressionForensics.pdf
 
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)
SIGGRAPH 2014 Course on Computational Cameras and Displays (part 3)
 
Semantic Segmentation - Fully Convolutional Networks for Semantic Segmentation
Semantic Segmentation - Fully Convolutional Networks for Semantic SegmentationSemantic Segmentation - Fully Convolutional Networks for Semantic Segmentation
Semantic Segmentation - Fully Convolutional Networks for Semantic Segmentation
 
TAME: Trainable Attention Mechanism for Explanations
TAME: Trainable Attention Mechanism for ExplanationsTAME: Trainable Attention Mechanism for Explanations
TAME: Trainable Attention Mechanism for Explanations
 
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)
Deep Neural Networks (D1L2 Insight@DCU Machine Learning Workshop 2017)
 
Overview of Convolutional Neural Networks
Overview of Convolutional Neural NetworksOverview of Convolutional Neural Networks
Overview of Convolutional Neural Networks
 
1-pytorch-CNN-RNN.pdf
1-pytorch-CNN-RNN.pdf1-pytorch-CNN-RNN.pdf
1-pytorch-CNN-RNN.pdf
 
Mask-RCNN for Instance Segmentation
Mask-RCNN for Instance SegmentationMask-RCNN for Instance Segmentation
Mask-RCNN for Instance Segmentation
 
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...
Image Segmentation with Deep Learning - Xavier Giro & Carles Ventura - ISSonD...
 
Spatial Filtering in intro image processingr
Spatial Filtering in intro image processingrSpatial Filtering in intro image processingr
Spatial Filtering in intro image processingr
 
Deep learning for image video processing
Deep learning for image video processingDeep learning for image video processing
Deep learning for image video processing
 
A brief introduction to recent segmentation methods
A brief introduction to recent segmentation methodsA brief introduction to recent segmentation methods
A brief introduction to recent segmentation methods
 

More from YuChianWu

lecture04_mle_svm_multiclass_pca.pdf
lecture04_mle_svm_multiclass_pca.pdflecture04_mle_svm_multiclass_pca.pdf
lecture04_mle_svm_multiclass_pca.pdfYuChianWu
 
lecture02_LinearRegression.pdf
lecture02_LinearRegression.pdflecture02_LinearRegression.pdf
lecture02_LinearRegression.pdfYuChianWu
 
week13_yolo_mobilenet.pdf
week13_yolo_mobilenet.pdfweek13_yolo_mobilenet.pdf
week13_yolo_mobilenet.pdfYuChianWu
 
week10_Reinforce.pdf
week10_Reinforce.pdfweek10_Reinforce.pdf
week10_Reinforce.pdfYuChianWu
 
week12_cv_intro_and_r-cnn.pdf
week12_cv_intro_and_r-cnn.pdfweek12_cv_intro_and_r-cnn.pdf
week12_cv_intro_and_r-cnn.pdfYuChianWu
 
Fragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdf
Fragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdfFragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdf
Fragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdfYuChianWu
 
Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...
Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...
Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...YuChianWu
 
Lets-Attack-Lets_Encrypt.pdf
Lets-Attack-Lets_Encrypt.pdfLets-Attack-Lets_Encrypt.pdf
Lets-Attack-Lets_Encrypt.pdfYuChianWu
 
A-Hole-in-the-Tube.pdf
A-Hole-in-the-Tube.pdfA-Hole-in-the-Tube.pdf
A-Hole-in-the-Tube.pdfYuChianWu
 
IPvSeeYou.pdf
IPvSeeYou.pdfIPvSeeYou.pdf
IPvSeeYou.pdfYuChianWu
 
kolmogorov_foundations.pdf
kolmogorov_foundations.pdfkolmogorov_foundations.pdf
kolmogorov_foundations.pdfYuChianWu
 
Introductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdf
Introductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdfIntroductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdf
Introductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdfYuChianWu
 

More from YuChianWu (12)

lecture04_mle_svm_multiclass_pca.pdf
lecture04_mle_svm_multiclass_pca.pdflecture04_mle_svm_multiclass_pca.pdf
lecture04_mle_svm_multiclass_pca.pdf
 
lecture02_LinearRegression.pdf
lecture02_LinearRegression.pdflecture02_LinearRegression.pdf
lecture02_LinearRegression.pdf
 
week13_yolo_mobilenet.pdf
week13_yolo_mobilenet.pdfweek13_yolo_mobilenet.pdf
week13_yolo_mobilenet.pdf
 
week10_Reinforce.pdf
week10_Reinforce.pdfweek10_Reinforce.pdf
week10_Reinforce.pdf
 
week12_cv_intro_and_r-cnn.pdf
week12_cv_intro_and_r-cnn.pdfweek12_cv_intro_and_r-cnn.pdf
week12_cv_intro_and_r-cnn.pdf
 
Fragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdf
Fragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdfFragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdf
Fragattacks-Breaking-Wi-Fi-Through-Fragmentation-And-Aggregation.pdf
 
Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...
Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...
Im-A-Hacker-Get-Me-Out-Of-Here-Breaking-Network-Segregation-Using-Esoteric-Co...
 
Lets-Attack-Lets_Encrypt.pdf
Lets-Attack-Lets_Encrypt.pdfLets-Attack-Lets_Encrypt.pdf
Lets-Attack-Lets_Encrypt.pdf
 
A-Hole-in-the-Tube.pdf
A-Hole-in-the-Tube.pdfA-Hole-in-the-Tube.pdf
A-Hole-in-the-Tube.pdf
 
IPvSeeYou.pdf
IPvSeeYou.pdfIPvSeeYou.pdf
IPvSeeYou.pdf
 
kolmogorov_foundations.pdf
kolmogorov_foundations.pdfkolmogorov_foundations.pdf
kolmogorov_foundations.pdf
 
Introductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdf
Introductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdfIntroductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdf
Introductory Real Analysis (A. N. Kolmogorov, S. V. Fomin etc.) (z-lib.org).pdf
 

Recently uploaded

Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...
Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...
Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...Call Girls Mumbai
 
Thermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptThermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptDineshKumar4165
 
Air Compressor reciprocating single stage
Air Compressor reciprocating single stageAir Compressor reciprocating single stage
Air Compressor reciprocating single stageAbc194748
 
kiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadkiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadhamedmustafa094
 
Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwait
Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills KuwaitKuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwait
Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwaitjaanualu31
 
AIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech studentsAIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech studentsvanyagupta248
 
Bridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptxBridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptxnuruddin69
 
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptxS1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptxSCMS School of Architecture
 
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptxCOST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptxJIT KUMAR GUPTA
 
data_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfdata_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfJiananWang21
 
DC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equationDC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equationBhangaleSonal
 
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments""Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"mphochane1998
 
notes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptnotes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptMsecMca
 
Computer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to ComputersComputer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to ComputersMairaAshraf6
 
A Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna MunicipalityA Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna MunicipalityMorshed Ahmed Rahath
 
Standard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayStandard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayEpec Engineered Technologies
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Arindam Chakraborty, Ph.D., P.E. (CA, TX)
 
Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086anil_gaur
 
Double Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torqueDouble Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torqueBhangaleSonal
 

Recently uploaded (20)

Call Girls in South Ex (delhi) call me [🔝9953056974🔝] escort service 24X7
Call Girls in South Ex (delhi) call me [🔝9953056974🔝] escort service 24X7Call Girls in South Ex (delhi) call me [🔝9953056974🔝] escort service 24X7
Call Girls in South Ex (delhi) call me [🔝9953056974🔝] escort service 24X7
 
Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...
Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...
Bhubaneswar🌹Call Girls Bhubaneswar ❤Komal 9777949614 💟 Full Trusted CALL GIRL...
 
Thermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.pptThermal Engineering -unit - III & IV.ppt
Thermal Engineering -unit - III & IV.ppt
 
Air Compressor reciprocating single stage
Air Compressor reciprocating single stageAir Compressor reciprocating single stage
Air Compressor reciprocating single stage
 
kiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal loadkiln thermal load.pptx kiln tgermal load
kiln thermal load.pptx kiln tgermal load
 
Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwait
Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills KuwaitKuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwait
Kuwait City MTP kit ((+919101817206)) Buy Abortion Pills Kuwait
 
AIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech studentsAIRCANVAS[1].pdf mini project for btech students
AIRCANVAS[1].pdf mini project for btech students
 
Bridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptxBridge Jacking Design Sample Calculation.pptx
Bridge Jacking Design Sample Calculation.pptx
 
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptxS1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
S1S2 B.Arch MGU - HOA1&2 Module 3 -Temple Architecture of Kerala.pptx
 
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptxCOST-EFFETIVE and Energy Efficient BUILDINGS ptx
COST-EFFETIVE and Energy Efficient BUILDINGS ptx
 
data_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdfdata_management_and _data_science_cheat_sheet.pdf
data_management_and _data_science_cheat_sheet.pdf
 
DC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equationDC MACHINE-Motoring and generation, Armature circuit equation
DC MACHINE-Motoring and generation, Armature circuit equation
 
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments""Lesotho Leaps Forward: A Chronicle of Transformative Developments"
"Lesotho Leaps Forward: A Chronicle of Transformative Developments"
 
notes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.pptnotes on Evolution Of Analytic Scalability.ppt
notes on Evolution Of Analytic Scalability.ppt
 
Computer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to ComputersComputer Lecture 01.pptxIntroduction to Computers
Computer Lecture 01.pptxIntroduction to Computers
 
A Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna MunicipalityA Study of Urban Area Plan for Pabna Municipality
A Study of Urban Area Plan for Pabna Municipality
 
Standard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power PlayStandard vs Custom Battery Packs - Decoding the Power Play
Standard vs Custom Battery Packs - Decoding the Power Play
 
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
Navigating Complexity: The Role of Trusted Partners and VIAS3D in Dassault Sy...
 
Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086Minimum and Maximum Modes of microprocessor 8086
Minimum and Maximum Modes of microprocessor 8086
 
Double Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torqueDouble Revolving field theory-how the rotor develops torque
Double Revolving field theory-how the rotor develops torque
 

week14_segmentation.pdf